The present application generally relates to devices for detecting mechanical strain. More particularly, the present application relates to a strain sensor that can detect strain based on changes in magnetic permeability of magnetic shape-memory alloy material with deformation. The apparatus can detect strain in one, two or three dimensions, and all six components of the strain tensor, and can also be used to detect mechanical stress and all six components of the stress tensor.
Low back pain and osteoarthritis are typical examples of musculoskeletal injury and disease affecting a vast number of people. Approximately 69 million and 27 million patients, respectively, suffer from these disabling conditions in the United States alone. Mechanical loading analyses are useful in identifying both the causes of these conditions, as well as appropriate prevention and treatment strategies. For example, by examining patients as they walk, researchers have been able to use mechanical loading analysis to identify an important link between patient knee adduction joint moments and prevalent medial knee joint osteoarthritis.
It is difficult to perform loading analyses without knowing how and to what extent external forces act on body segments. Consequently, it is desirable accurately to measure external forces in three dimensions. Such macroscopic biomechanical loading information is also helpful in cell- or tissue-level analyses to estimate realistic in vivo microscopic loading conditions.
Unfortunately, external force measurements are not always straightforward, especially when obtaining reaction forces during dynamic motor activities. This is because researchers can usually only gather uninterrupted force information when a subject constrains his or her motor activity to always interact with an embedded sensor. Using floor-embedded force platforms to gather Ground Reaction Force (GRF) data during biped activities is a typical approach. These types of facilities sometimes offer limited data quality and quantity. For example, floor-embedded force platforms can suffer from contact problems, present unrealistic conditions, and only give short duration data. Additionally, while insole pressure sensors are currently available, many devices that are currently available detect only a single, vertical force component. With this information, it is difficult for researchers to obtain accurate, clinically relevant kinetic variables such as joint moments and joint contact forces, which can be used to examine a variety of injuries and diseases such as joint and connective tissue injuries, osteoarthritis, and motor dysfunctions such as cerebral palsy, stroke, and Parkinson's disease.
The present disclosure is directed to addressing one or more of the above issues.